Title :
An Adaptive Detection Algorithm
Author_Institution :
Lincoln Laboratory
fDate :
3/1/1986 12:00:00 AM
Abstract :
A general problem of signal detection in a background of unknown Gaussian noise is addressed, using the techniques of statistical hypothesis testing. Signal presence is sought in one data vector, and another independent set of signal-free data vectors is available which share the unknown covariance matrix of the noise in the former vector. A likelihood ratio decision rule is derived and its performance evaluated in both the noise-only and signal-plus-noise cases.
Keywords :
Colored noise; Covariance matrix; Detection algorithms; Detectors; Gaussian noise; Interference; Matched filters; Signal detection; Signal to noise ratio; Testing;
Journal_Title :
Aerospace and Electronic Systems, IEEE Transactions on
DOI :
10.1109/TAES.1986.310745
